Internet of Things (IoT), Blockchain, Robotics and AI are finally a reality. It’s a marvel to construe that machines of today can actually learn, improve over a period of time with an in-built self-learning capability.
Article Authored by Snehal Desai, Global Sales Head – Insurance, 3i Infotech
Mankind’s quest for Artifical Intelligence (AI) has driven development from times immemorial. It dates back to the architectural astronomy instruments in India to Abacus of Mesopotamia; from mechanical triggering of medieval cannons in China to the emergence of the big World Wide Web; and finally to the 21st century when Internet of Things (IoT), Blockchain, Robotics and AI are finally a reality. It’s a marvel to construe that machines of today can actually learn, improve over a period of time with an in-built self-learning capability.
AI not only refers to a specific software algorithm but a broad spectrum of capabilities of machines that have cognitive functions, which include speech recognition, machine translation, file reading from a machine, fraud detection prediction, learning and predicting trends and natural language processing. A recent report suggests that globally over $1 trillion of today’s financial services cost structure could be replaced by machine learning and AI.
Financial institutions worldwide have always been at the forefront of adopting new technology. Closer home, in India, recent reports published by Accenture suggest that around 83% of Indian bankers believe that AI will work alongside humans in the next two years, which is higher than the global average of 79%.
Let’s delve deeper into how AI in the set to transform Banking and Insurance of the future. Focus on the how AI would be integrated into BFSI, the many benefits and use-cases to substantiate how the ecosystem would evolve.
Customer Service Chatbots
Smart virtual agents or chatbots elevate the customer experience to a new level by providing real-time round with the clock service with natural language to perform day to day transactions. They anticipate customers unique transaction needs and recommend the right insurance policy or right portfolio for investment in a fraction of a second, with the quick ability to deep dive into the data models. This gives customer personalised services experience and increased customer satisfaction.
Customer & Business Audio Bots
A case in point, is a customer greeted by EVA from Emirates NBD (leading bank in UAE), an audio bot. This is a new face of banking where audio bots are taking over in a quick and efficient way to provide information. Bots can run query much faster and provide results to the customer objectively, without any emotions attached to it. There is a growing demand for audio bots within businesses. In a typical scenario, a CEO can be remotely assisted by an audio bot to provide him sales performance data of a branch or a zone, provide instant details about top performers, top claims paid or on the business forecast for the year.
Virtual assistants can manage the low-value activities of advisors, such as lead management, scheduling, planning, licensing, etc., enabling them to focus on building skills and providing value-added services.
Companies have transformed from the conventional password and I pin methods to voice recognition with the help of voice prints to automate the process. Face recognition to ascertain account credentials are becoming a norm.
Customer Insights and Risk Management
Risk management is one of the largest opportunity for leveraging the full potential of AI. Using AI in Banking it is possible to sieve through different data sources such as credit scores, financial data, spending patterns help to determine risk scores of a customer, based on his or her nationality, occupation, salary range, experience, industry and credit history. Moreover, AI can be used to reduce the strain of regulatory compliance and to overhaul the way banks/insurers detect financal crimes and frauds.
Similarly in Insurance, risk scores can be very helpful in underwriting policy and adjudicating claims for a individual on basis of various parameters. It could be based on data models during the onboarding of a customer, agent or a claim risk propensity can be calculated and early warning signals can be triggered.
AI systems can be used to perform research, aggregate, refine and present required information to underwriters, allowing them to focus on core underwriting activities.
Key benefits of AI
Enhance operational efficiency, improve time-to-market, enable a more intelligent way to sell and service, and more. During the last five years, industrial use of AI – in terms of interest, investment, ideation and implementation – has risen exponentially.
The proof of the pudding is in the eating. This can be validated through how a leading health insurance startup leveraged AI by using data and software to build clinical profiles of people to identify gaps in care. These gaps in care were filled with visits and free choice of doctors for patients to avoid costly hospital stays. Similarly, a life insurance startup used AI to generate quotes for accident death claims which simplified sign-up in less than 2 minutes. There are several such instances that fortify AI as a technology that would revolutionise businesses and the world at large.